where \(L_{cls}\)  contains the sum of Region Proposal Network (RPN) and Region of Interest (RoI) classification losses, while \(L_{reg}\)  contains the sum of RPN and RoI regression losses.
The \(L^{IoU}\)  loss will be defined in Subsection REF .
\(\alpha \) , \(\beta \)  and \(\gamma \)  represent how much weight each component of the unsupervised training has.
The new terms introduced in this paper, w.r.t. the ones defined in [1]}, are shown in bold in the above equations and will be described in the following.
